Distribution System Restoration via Subgradient-Based Lagrangian Relaxation

Perez-Guerrero, R.E.; Heydt, G.T.

doi:10.1109/tpwrs.2008.926471

Cited by 39 publications

(19 citation statements)

References 16 publications

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“…The single switching constraint is one of the most important constraints of the DSR problem which is considered in the method presented in this paper as well as several previous studies including Pérez‐Guerrero and Pérez‐Guerrero and Heydt . On the other hand, the switching cost is considered to be infinity in this study, similar to the previous ones.…”

Section: Deterministic Load Restoration Problemmentioning

confidence: 79%

A dynamic programing‐based framework for distribution system restoration considering load uncertainties

Riahinia

Abbaspour

Farzin

et al. 2017

Int Trans Electr Energ Syst

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Summary This paper presents a stochastic framework to properly involve the uncertainties associated with demand in distribution system restoration (DSR) problem. To reach this goal, these uncertainties are represented as probabilistic scenarios corresponding to different load levels. Subsequently, the associated stochastic optimization problem is formulated such that it can be readily solved using dynamic programming approach. Moreover, a clustering technique is presented that enables the dynamic programming approach to find near‐optimal solutions for the stochastic load restoration problem with reasonable computational effort. The proposed framework is implemented on a real‐world test system, and its efficiency and effectiveness are demonstrated through extensive case studies. The results suggest that incorporation of load uncertainties in the DSR problem would significantly affect the optimal sequence of feeder restoration, and therefore, appropriate treatment of load uncertainties in DSR problem is essential.

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Section: Deterministic Load Restoration Problemmentioning

confidence: 79%

A dynamic programing‐based framework for distribution system restoration considering load uncertainties

Riahinia

Abbaspour

Farzin

et al. 2017

Int Trans Electr Energ Syst

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“…Ref. [20] applies LR to the optimal restoration problem of distribution systems after a blackout occurs. Ref.…”

Section: Introductionmentioning

confidence: 99%

Solving corrective risk-based security-constrained optimal power flow with Lagrangian relaxation and Benders decomposition

Wang¹,

McCalley

Zheng³

et al. 2016

International Journal of Electrical Power & Energy Systems

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“…While monitoring the power systems and identifying the connectivity of the system, the path for restoration is searched. The transmission lines and transformers on the paths are re-energized, and the load is restored depending on the system balance [12][13][14]. During the restoration stage, three limitations are needed to maintain the range: the voltage of the bus, the overload rate of the transmission lines and the frequency of the grid.…”

Section: Introductionmentioning

confidence: 99%

Development of a Sequential Restoration Strategy Based on the Enhanced Dijkstra Algorithm for Korean Power Systems

2016

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When a blackout occurs, it is important to reduce the time for power system restoration to minimize damage. For fast restoration, it is important to reduce taking time for the selection of generators, transmission lines and transformers. In addition, it is essential that a determination of a generator start-up sequence (GSS) be made to restore the power system. In this paper, we propose the optimal selection of black start units through the generator start-up sequence (GSS) to minimize the restoration time using generator characteristic data and the enhanced Dijkstra algorithm. For each restoration step, the sequence selected for the next start unit is recalculated to reflect the system conditions. The proposed method is verified by the empirical Korean power systems.

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Distribution System Restoration via Subgradient-Based Lagrangian Relaxation

Cited by 39 publications

References 16 publications

A dynamic programing‐based framework for distribution system restoration considering load uncertainties

A dynamic programing‐based framework for distribution system restoration considering load uncertainties

Solving corrective risk-based security-constrained optimal power flow with Lagrangian relaxation and Benders decomposition

Development of a Sequential Restoration Strategy Based on the Enhanced Dijkstra Algorithm for Korean Power Systems

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